69737 - Business Performance Analytics

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Decent work and economic growth Industry, innovation and infrastructure

Academic Year 2022/2023

Course contents

Module 1 - Business Performance Analytics

  1. Performance Measurement Systems, Performance Management Systems, Performance Management Analytics
  2. Business performance analytics: definition and areas of application
  3. Type of business performance analytics: supply chain analytics, internal analytics, customer analytics, external analytics
  4. Financial analytics, cost analytics, revenue analytics
  5. Strategic management accounting techniques for business performance analytics
  6. Analytical tools for business analysis and performance management
  7. The design of business performance analytical system

Module 2 - Business intelligence

  1. Introduction to Information Systems
  2. From process to data
  3. IS classification
    • The application portfolio
    • CIM systems
    • ERP systems
    • CRM systems
  4. Business intelligence:
    • the role of BI in the corporate information system;
    • the BI pyramid.
  5. Data Warehousing:
    • architectures;
    • techniques for data analysis;
    • lifecycle:
      • data source analysis;
      • requirement analysis;
      • conceptual design;
      • workload and data volume;
      • logical design;
      • design of ETL procedures;
      • physical design.

Readings/Bibliography

Slides

Articles (TBA)

Book chapters (TBA)

Details will be available in the e-learning web site of the course

Teaching methods

Lectures, seminars and case studies analysis

Assessment methods

Written test and project work (Module 1)

Written test with open questions and exercises (module 2)

Grades are assigned on the basis of an overall assessment of knowledge, skills, presentation and discussion skills of the topics covered. The ranges of grades correspond can be described as follows:

18-23: the student has sufficient preparation and analytical skills, spread however, over just few topics taught in the course, the overall jargon is correct

24-27: the student shows and adequate preparation at a technical level with some doubts over the topics. Good, yet not to articulate analytical skills with the use of a correct jargon

28-30: Great knowledge about most of the topics taught in the course, good critical and analytical skills, good usage of the specific jargon

30L: excellent and in depth knowledge of all the topics in the course, excellent critical and analytical skills, excellent usage of specific jargon

Teaching tools

Powerpoint class presentations, laboratory and use of analytics software, additional readings, sources and information about the program, case studies are available in the e-learning web site ( https://elearning-cds.unibo.it [http://https//elearning-cds.unibo.it] )

Office hours

See the website of Riccardo Silvi